Method and system for qualitatively and quantitatively analyzing experiences for recommendation profiles

ABSTRACT

Example embodiments include User Experience Analysis (UEA) system and method. The system and method are employed to qualitatively and quantitatively analyze user experiences, in order to provide electronic content recommendations. The system and method may be employed to provide user specific content recommendations that are based on a determined value-congruence, or relevancy, between electronic content and the recommendation profile generated for the user. The recommendation profile may be determined based on qualitatively and quantitatively analyzing positive appraisal sensations. The positive appraisal sensations may be associated with the user&#39;s physiological and/or psychological responses to predetermined content consuming experiences presented to the user, according to the embodiments.

CROSS-REFERENCE TO PROVISIONAL APPLICATION

This application claims priority to U.S. Provisional Application61/928,780, filed on Jan. 17, 2104, the disclosure of which isincorporated by reference into the present application in its entirety.

TECHNICAL FIELD

This application to systems and methods for analyzing qualitative andquantitative user experience data for providing recommendations ofcontent.

BACKGROUND OF THE INVENTION

Large amounts of multimedia content, such as movies, music, and video,which are all readily accessible to users via the Internet can causedifficulties for users attempting to find particularly relevant content.Many users find searching through the vast quantities of content, muchof the content comprising divergent types and categories, to be bothcumbersome and time consuming. These situations have caused techniquesfor effectively recommending target information to become vital in thearea of on-line content. Specifically, by efficiently recommendingsignificantly smaller amounts of content (e.g., multimedia content),which may be considered relevant by a user, these mechanisms canconsiderably reduce that amount of information content e.g., that has tobe searched, downloaded, or viewed by the user.

Current mechanisms for providing recommendations in popular contentprovider systems such as Netflix and Amazon are based on on-linepurchasing histories and browsing histories of existing users. Forexample, Netflix, a provider of on-line movies, recommends a list ofmovies to be viewed by the current user based on the predeterminedbrowsing history of other users. The recommendation is consideredrelevant, as it is based on existing users who also previously viewedthe same movie as the current user. However, these known recommendationtechniques generally rely on the responses and behaviors of variousdifferent users that may not be similar to that of the current user.Thus, recommendations provided using this aforementioned technique maynot provide the content which is considered most relevant, orentertaining, to the user.

SUMMARY OF THE INVENTION

An example embodiment includes a method, including the steps of:initiating, by one or more computing devices, a user experienceassessment with a user computer via a communications network, whereinthe user experience assessment comprises one or more predeterminedcontent consuming experiences; receiving, by the one or more computingdevices, positive appraisal sensation data from the user computer,wherein the positive appraisal sensation data comprises user responsesassociated with the one or more predetermined content consumingexperiences; analyzing, by the one or more computing devices, thepositive appraisal data using a qualitative analysis algorithm and aquantitative analysis algorithm; determining, by the one or morecomputing devices, one or more positive appraisal categoriescorresponding to the positive appraisal data, wherein the one or moreappraisal categories are determined based on the analysis; generating,by the one or more computing devices, a recommendation profileassociated with the user, wherein the recommendation profile comprisesthe one or more positive appraisal categories; determining, by the oneor more computing devices, whether one or more matches exist between therecommendation profile and coded content; generating, by the one or morecomputing devices, content recommendation information based on thedetermined matches; and transmitting, by the one or more computingdevices, an electronic message to the user via the communicationsnetwork, wherein the electronic message comprises the contentrecommendation information.

An example embodiment includes a system, having: a communicationsnetwork; a user computer commutatively coupled to the communicationsnetwork; and one or more computing devices communicatively coupled tothe communications network, wherein the one or more computing devicesoperates to: initiate a user experience assessment with the usercomputer via the communications network, wherein the user experienceassessment comprises one or more predetermined content consumingexperiences; receive positive appraisal sensation data from the usercomputer, wherein the positive appraisal sensation data comprises userresponses associated with the one or more predetermined contentconsuming experiences; analyze the positive appraisal data using aqualitative analysis algorithm and a quantitative analysis algorithm;determine one or more positive appraisal categories corresponding to thepositive appraisal data, wherein the one or more appraisal categoriesare determined based on the analysis; generate a recommendation profileassociated with the user, wherein the recommendation profile comprisesthe one or more positive appraisal categories; determine whether one ormore matches exist between the recommendation profile and coded content;generate content recommendation information based on the determinedmatches; and transmit an electronic message to the user computer via thecommunications network, wherein the electronic message comprises thecontent recommendation information.

Furthermore, current recommendation mechanisms fail to explore theintersection of psychological, biological, and computer sciences inorder to consider intrinsically motivated, receptive, emotional markersthat are identifiable during consumer experiences such as watchingmovies, reading books, vacationing, dining, or watching television.These experiences are directly related to individuals' emotional traits,and can be incorporated into recommendation algorithms for furtherquantitative and qualitative analysis to measure for both well-being andloyalty.

Therefore, there is a need for a method and a system employed forproviding recommendations based on the qualitative and quantitativeanalysis of experiences directly related to the user for which therecommendation is provided. Thus, multimedia content included inrecommendations, in accordance with the example embodiments, arepotentially more personalized and appropriate for the user.Consequently, the example embodiments provide increased usersatisfaction based on analyzing the experiences of the recommended user.

These and other drawbacks exist.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a system for performing qualitatively andquantitatively analysis of user experiences in order to provide contentrecommendations, in accordance with an example embodiment.

FIG. 2 illustrates internal components of a User Experience Analysis(UEA) system for performing qualitatively and quantitatively analysis ofuser experiences in order to provide content recommendations, inaccordance with an example embodiment.

FIG. 3 illustrates data model for organizing and maintaining positiveappraisal data in accordance with and example embodiments.

FIGS. 4A-4B illustrate a flow diagram of the method for performingqualitatively and quantitatively analysis of user experiences in orderto provide content recommendations, in accordance with exampleembodiments.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

It will be readily understood by those persons skilled in the art thatthe various embodiments described herein are capable of broad utilityand application.

Example methods are provided by way of example herein, as there are avariety of ways to carry out the method disclosed herein. The methodsdepicted in the Figures may be executed or otherwise performed by one ora combination of various systems, such as described herein. Each blockshown in the Figures represents one or more processes, methods, and/orsubroutines carried out in the example methods. Each block may have anassociated processing machine or the blocks depicted may be carried outthrough one processor machine. Furthermore, while the steps may be shownin a particular order, it should be appreciated that the steps may beconducted in a different order.

The description of example embodiments describes servers, portableelectronic devices, and other computing devices that may include one ormore modules, some of which are explicitly depicted in the figures,others are not. As used herein, the term “module” may be understood torefer to executable software, firmware, hardware, and/or variouscombinations thereof. It is noted that the modules are example. Themodules may be combined, integrated, separated, and/or duplicated tosupport various applications. Also, a function described herein as beingperformed at a particular module may be performed at one or more othermodules and/or by one or more other devices (e.g., servers) instead ofor in addition to the function performed at the particular module.Further, the modules may be implemented across multiple devices and/orother components local or remote to one another. Additionally, themodules may be moved from one device and added to another device, and/ormay be included in both devices. It is further noted that the softwaredescribed herein may be tangibly embodied in one or more physical media,such as, but not limited to, a compact disc (CD), a digital versatiledisc (DVD), a floppy disk, a hard drive, read-only memory (ROM), randomaccess memory (RAM), as well as other physical media capable of storingsoftware, and/or combinations thereof. Moreover, the figures illustratevarious components (e.g., servers, portable electronic devices, clientdevices, computers, etc.) separately. The functions described as beingperformed at various components may be performed at other components,and the various components may be combined and/or separated. Othermodifications also may be made.

According to example embodiments, the systems and methods may becomputer implemented using one or more computers, incorporating computerprocessors. The computer implementation may include a combination ofsoftware and hardware. The computers may communicate over acomputer-based network. The computers may have software installedthereon configured to execute the methods of the example embodiments.The software may be in the form of modules designed to cause a computerprocessor to execute specific tasks. The software may be stored on atangible, non-transitory computer-readable medium. The computers may beconfigured with hardware to execute specific tasks. As should beappreciated, a variety of computer-based configurations are possible.

FIG. 1 is a system for analyzing qualitative and quantitative userexperience data for providing recommendations of content, according toexample embodiments. The system 100 may provide various functionalityand features of the User Experience Analysis (UEA) system 110. Accordingto an embodiment, the system 100 may be employed for qualitatively andquantitatively analyzing user experiences for providing recommendationsof content. Specifically, the system 100 may support collecting, andsubsequently analyzing, user specific information which relates humanreactions (e.g., physiological, psychological, etc.) to variousexperiences. In an embodiment, positive appraisal experiences mayinclude consuming particular types of content. Thereafter, the systemmay provide content recommendations based on a determinedvalue-congruence between identified user reactions and correspondinglycategorized content. The system 100 may include one or more usercomputers 105, a UEA system 110, a communications network 115, arecommendation profile database 120, and a content database 125.

According to an embodiment, the UEA system 110 may be connected to acommunications network 115. The communications network may include oneor more servers and/or computer processors. For example, thecommunications network 115 may be a wide area network (WAN), such as theInternet or a network connected to the Internet. The network may be asatellite or cellular-based network. Information and data may beexchanged through the network between the various devices. Furthermore,the communications network 115 may be a local area network (LAN), suchas an intranet. It should be appreciated that the network may be acombination of local area networks, wide area networks, and externalnetworks, which may be connected to the Internet.

In accordance with example embodiments, a plurality of user computers105 may be connected to communications network 115 and the UEA System110. The user computer 105 may be a personal computer such as desktopcomputer, running software which facilitates data collection andcommunications with the UEA system 110. The user computer 105 may beused to control and/or communicate with the UEA system 110.

Further, various technologies may be used to provide communicationbetween the various processors and/or memories, as well as to allow theprocessors and/or the memories of the various embodiments to communicatewith any other entity; e.g., so as to obtain further instructions or toaccess and use remote memory stores, for example. Such technologies usedto provide such communication might include a network, such as acomputer network, for example, the Internet, Intranet, Extranet, LAN, orany client server system that provides communication of any capacity orbandwidth, for example. Such communications technologies may use anysuitable protocol such as TCP/IP, UDP, or OSI, for example. It should beappreciated that examples of computer networks used in the precedingdescription of example embodiments, such as the Internet, are meant tobe non-limiting and example in nature.

According to an embodiment, software installed on the user device 105may include real-time telecommunication applications and/or applicationsuites, such as videoconferencing and webinar applications. Softwareexecuted on the user computer 105 may further provide an interface thatallows the user to perform a wide variety of actions involvingnetwork-based access, retrieval, and/or consumption of content. Forinstance, the user computer 105 may use software, such as Windows MediaPlayer, for downloading and viewing movies from the Internet. Additionaldevices may be either wired or wirelessly coupled to the user computer105 in order perform various functions. For example, a biofeedbacksensor may be connected to the user computer 105 which enables a user'sphysiological activity, such as brain waves, to be monitored and/ormeasured.

According to an embodiment, the user computer 105 may be one or moreportable data processing platforms or portable electronic devices. In anexample embodiment, each user computer 105 may be a portable electronicdevice or mobile electronic device. The portable electronic device mayhave communication capabilities over cellular, wireless, and/or wiredtype networks to transmit/receive data and/or voice communications.

The portable electronic device, by way of non-limiting examples, mayinclude such portable computing and communications devices as mobilephones (e.g., cell or cellular phones), smart phones (e.g., iPhones,Android based phones, or Blackberry devices), personal digitalassistants (PDAs) (e.g., Palm devices), laptops, netbooks, tablets, orother portable computing devices. These portable electronic devices maycommunicate and/or transmit/receive data over a wireless signal. Thewireless signal may consist of Bluetooth, Wireless Application Protocol(WAP), Multimedia Messaging Service (MMS), Enhanced Messaging Service(EMS), Short Message Service (SMS), Global System for MobileCommunications (GSM)-based systems, Code Division Multiple Access(CDMA)-based systems, Transmission Control Protocol/Internet Protocols(TCP/IP), or other protocols and/or systems suitable for transmittingand receiving data from the portable electronic device. The portableelectronic device may use standard wireless protocols which may includeIEEE 802.11a, 802.11b, 802.11g, 802.11n, Near-Field Communications, andBluetooth. Certain portable electronic devices may be Global PositioningSystem (GPS) capable. Other location systems may be used. The portableelectronic device may include one or more computer processors and becapable of being programmed to execute certain tasks.

According to an embodiment, the UEA system 110 may be one or morecomputers, such as personal computers. In another embodiment, the UEAsystem 110 may include one or more servers. The UEA system 110 mayinclude the functionality of a server system, such as, a UNIX basedserver, Windows 2000 Server, Microsoft IIS Server, Apache HTTP server,API server, Java server, Java Servlet, API server, ASP server, PHPserver, HTTP server. Mac OS X server, Oracle server, IP server, or otherindependent server. For instance, a user (e.g., experience assessmentadministrator) may employ a computer communicatively connected to theUEA system 110 to further control and/or operate the functions supportedby the one or more servers. According to an embodiment, the UEA system110 may be one or more portable data processing platforms or portableelectronic devices.

In an embodiment, the UEA system 110 may include conventional real-timetelecommunication applications and/or application suites, to supportnetwork-based communications. The application suite and platform of theUEA system 110 may be employed to conduct network-based experienceassessments, for example a WebEx session. The real-time communicationmay enable the UEA system 110 to distribute and receive positiveappraisal data for analysis. The telecommunication applications mayimplement any mechanism that functions to transmit and/or receive audio,visual, and/or multimedia information.

According to an embodiment, software may be installed on the UEA system110 that enables database management system (DBMS) operations to beperformed. DBMS related programs may enable the UEA system 110 tooperatively communicate with databases in order to store, modify, andextract information. The UEA system 110 software may also be employed tocreate and manipulate various data structures. For examples, queues maybe employed for arranging and/or organizing the received positiveappraisal experiences, positie appraisal sensations, and other data fromthe user computers 105. In an embodiment, the UEA system 110 maycommunicate with content database 125 and recommendation profiledatabase 120 to store and/or retrieve data.

In an embodiment, the UEA system 110 may have a log-in associatedtherewith. The log-in may be used to allow access to the system. Thelog-in may require a particular input or it may accept a combination ofinputs. The input may serve as an authentication of the user to thesystem and, in some embodiments, the system 100 in general. Variousauthentication or log-on systems and methods may be used. For example,these methods and systems may include entering a password or PersonalIdentification Number (PIN) or using a card to logon, either via swipingthe card through a reader, such as a magnetic stripe reader or a smartchip reader, or through a radio frequency system (which may require thatthe card be placed in proximity to an appropriate reader (e.g., acontactless system), such as, for example, Radio FrequencyIdentification (RFID) or Near Field Communications (NFC). It should beappreciated that the card may include a combination of a magnetic strip,a smart chip, and radio frequency. Further, the use of the card isexample only and the card may include fobs, stickers, and other devices.Biometrics may be used, such as fingerprints, facial recognition, speechrecognition, palm vein scan, or retinal scan. A combination of thesesystems may be used. Biometrics may be used in addition to other log-inmethods and systems.

Recommendation profile database 120 and content database 125 may beinterconnected to the UEA system 110, and/or one or more user computers105 via communications network 110. The recommendation profile database120 and content database 125 may be implemented as external storagedevices, for example database servers. Though illustrated as separate,the functionality and content of the recommendation profile database 120and/or the content database 125 may be integrated into the UEA system.In an embodiment, the databases may be included as internal storagedevices for the UEA system 110. The recommendation profile database 120may include one or more recommendation profiles that have been createdby the UEA system 110 using qualitative and quantitative analysis.Accordingly, the recommendation profiles may each be comprised ofcategorized positive appraisal sensations for the corresponding user.The recommendation profiles may serve to indicate the user's behaviorand preferences in order to support content recommendation capabilitiesof the embodiments.

The content database 125 may include a plurality of audio, visual,and/or or multimedia electronic content. Content stored by the contentdatabase 125 may be various forms of multimedia data. The content may betransmitted to the user computer 105 and/or the UEA system 110 via thecommunications network 115. In an embodiment, the content may besubsequently consumed (e.g., purchased, viewed, heard, read, etc.) by auser. Examples of content include, but are not limited to, movies,books, video, television, music, and other forms of multimedia data. Forpurposes of illustration, the example embodiment discussed may involveson-line (e.g., Internet accessible) movie content. The content stored incontent database 120 may be pre-categorized and/or categorized by theUEA system 110 according to associated content categories. In exampleembodiments, the value-congruence and content recommendation functionsof the UEA system 110 may be implemented by retrieving and processingthe categorized content in content database 125 and the recommendationprofiles in recommendation profile database 120.

In an embodiment, the content database 125 may contain content from oneor more data sources that may provide a plurality of information,services, and/or products via a communications network, such as theInternet. Data sources may include various distributors such as contentproviders, search engines, document listing providers, an electroniccontent source, a website host, and any other source that may serve toprovide electronic content to users. According to the embodiment, theone or more data sources may transmit, or otherwise distribute, contentto the content database 125.

In an embodiment, the content database 125 may include various databasecreating and managing functions. The database capabilities of thecontent database 125 may be implemented using various special-purposeprogramming languages, such as Structured Query Language (SQL), that maybe designed for managing the data maintained by the content database125. Thereafter, one or more software applications, for exampleApplication Programming Interfaces (API), may be employed in order todefine the particular capability, such as data mining, that may beemployed by the content database 125. In an embodiment, the contentdatabase 125 capabilities may allow the stored content to be evaluatedand subsequently manipulated. Content may be evaluated, for example textscanned, in order to retrieve information that may be further used todetermine patterns, relationships, and characteristics that may beassociated with the content. For example, the content database 125, mayoperate to text scan an electronic book, in order to recognize varioustext strings, and subsequently characterize the e-book as containing“humor.” Accordingly, the content database 125 may operate to organize,for example separate and/or aggregate, the stored content according tocharacteristics resulting from performing the evaluation capabilities.The content database 125 may also be capable of creating models and/orgraphical representations of the data in order to perform the one ormore evaluation functions.

In an embodiment, the content database 125 may operate to automaticallydata mine a plurality of content providers for content. Thereafter, themined content may be stored in the content database 125 itself, so as tobe available to user of the UEA system. The content database 125 mayalso mine data related to the content, such as metadata. Data related tocontent may be any information that may serve to describe, or otherwisecharacterize, the data, such as programming language, title, source, andthe like. The content database 125 may include functionality toautomatically access content and/or metadata from the data sources. Asan example, the content database 125 may automatically mine an on-linemovie provider for metadata related to the content of 100,000 movies.The content database 125 may evaluate the metadata, so as to create andmaintain various categories for the content. The movies, and anysubsequently retrieved content, may be stored and maintained accordingto these content categories.

Each of the system devices 105, 110, 120, and 125 may establishcommunications with other parts of the system 100 over thecommunications network 115 as described above. The devices 105, 110,120, and 125 may be geographically dispersed. Conversely, two or more ofdevices 105, 110, 120, and 125 may be located in close proximity. Uponsuccessful initiation of communications between the network 115 andanother part of the system 100, data may be exchanged between thevarious devices.

FIG. 2 depicts the components of the UEA system 200 for performingqualitatively and quantitatively analysis of user experiences in orderto provide, for example, content recommendations in accordance withexample embodiments.

The UEA system 200 may contain one or more hardware and softwarecomponents in the internal configuration as depicted in FIG. 2. Aprocessor 201 may be configured to control the functions of the UEAsystem 200. The processor 201 may execute software, firmware, andcomputer readable instructions stored in memory 202, such that thecapabilities of the UEA system 200 are implemented according to exampleembodiments. Memory 202 may include non-volatile and/or volatile memory.

The UEA system 200 may include one or more input/output devices 204 thatare capable of receiving and/or outputting information. In anembodiment, the input/output devices 204 may include a display and aninput device. The input/output device 204 may be a single device or acombination of devices.

The display may be monochrome or color. For example, the display may bea plasma, liquid crystal, or cathode ray tube type display. The displaymay be a touch screen type display. The UEA system 200 may have morethan one display. The multiple displays may be different types ofdisplays. The display may have sub-displays thereon. For example, thedisplay may have a large display surface. The display for the userinterface may occupy a portion or less than the whole of the largedisplay surface.

Input devices may include a keyboard, which can be a full-sized QWERTYkeyboard or a condensed keyboard. Input devices may further include anumeric pad, an alpha-numeric pad, a trackball, a touchpad, a mouse,and/or fixed selection buttons. As described above, the display mayserve as an input device through using or incorporating a touchscreeninterface.

In some embodiments, the input/output devices 204 may include one ormore cameras, optical sensors, biofeedback sensors, or other sensingdevices.

The interface 205 may be employed to commutatively couple the internalhardware and software components of the UEA system 200. The interface205 can be, for example but not limited to, one or more buses or otherwired or wireless connections, as is known in the art.

The UEA system 200 may include a positive appraisal collection module206. According to an example embodiment, one or more positive appraisalsensations may be collected by the UEA system 200 in response toconducting an experience assessment with the user. In the embodiments,positive appraisal data may be considered any sensation, such asphysiological activity, that may be positively identified and/ormeasured from the user. Positive appraisal sensations may be associatedwith human emotions that may be connotatively considered positive ornegative. Examples of positive appraisal sensations may include, but arenot limited to, happiness, fear, joy, anger, bravery, warmth, tingling,and the like. One or more positive appraisal sensations experienced bythe user may be transmitted to (e.g. biofeedback sensor), and/or enteredinto (e.g., I/O device) the UEA system 200. The positive appraisalsensations may be conveyed to the positive appraisal collection module206 by any communications medium, such as electrical signals, forexample. Furthermore, electronic transmission may be initially receivedvia a communications network, for example, by a suitable UEA systemcomponent. The input/output device 204 or a network interface, forinstance, may function to receive the positive appraisal sensations.Accordingly, the received positive appraisal sensations may beelectronically transferred to the positive appraisal collection module206 for storage. In an embodiment, the positive appraisal collectionmodule 206 may store the collected quantitative appraisal data and thequalitative appraisal data separately. Thereafter, the positiveappraisal collection module 206 may operate to store the collectedpositive appraisal sensations using various temporary and/or persistentstorage mechanisms. The positive appraisal collection module may operateto organize a plurality of collected appraisal data according to variousgrouping factors, including but limited to, the user, the positiveappraisal experience, the experience assessment, or any other categorythat may be deemed appropriate and/or necessary.

A positive appraisal analysis module 207 may be employed toqualitatively and quantitatively analyze the collected positiveappraisal data. The positive appraisal analysis module 207 may receive,and subsequently parse, the positive appraisal data received from thepositive appraisal collection module 206. Thereafter, the positiveappraisal analysis module 207 may evaluate the received positiveappraisal data. In an embodiment, a triangulation algorithm may beemployed as a mechanism to cross-validate data from the qualitativeand/or quantitative segments of the positive appraisal sensation data.The positive appraisal analysis module 207 may employ variousqualitative and/or quantitative algorithms in order to identifyclassifications of positive appraisal sensations, namely positiveappraisal sensation categories.

The qualitative analysis module 207 may further analyze positiveappraisal categories. The qualitative analysis module 207 may operate todetermine an ordered sequence of the identified positive appraisalcategories, based on one or more factors. Examples of sequencesdetermined by the qualitative analysis module 207 may include rating,ranking, weighing, and the like. In an embodiment, the qualitativeanalysis module 207 may employ an algorithm, such as a raking algorithm,to determine a rank corresponding to each positive appraisal category. Arank may be calculated based on a total number of occurrences associatedwith the positive appraisal category, for instance. Various knownalgorithms may be employed to rank, or otherwise order, the one or morepositive appraisal categories.

A value-congruence module 208 may be included. The value-congruencemodule 208 may be employed to further evaluate the analyzed positiveappraisal data, so as to generate a context specific recommendationprofile. Subsequently, the value-congruence module 208 may performvarious comparisons between the generated recommendation profile andpreviously coded content. The comparisons may be text based, forexample. Further, comparisons may be applied to one or more segments ofpositive appraisal data which comprise the recommendation profile andthe coded content. In some embodiments, the value-congruence module 208may consider factors derived from, or otherwise associated with, thepositive appraisal data such as various parameters, rankings,attributes, classifications, and the like.

In an embodiment, the value-congruence module 208 may determinevalue-congruency by identifying that a positive appraisal categoryincluded in a recommendation profile matches a category indicated by thecoded content. For example, the value-congruence module 208 may identifythe same positive appraisal category of “humor” in the recommendationprofile and a code associated with a particular content item. In thisinstance, the value-congruence module 208 considers value-congruency toexist between the recommendation profile and the content. In someembodiments, the value-congruence module 208 may require one match, or apredetermined number of matches, to be identified in order to determinevalue-congruency. Alternatively, other evaluations may be employed, forexample percentages or thresholds, for value-congruency to bedetermined. It should be appreciated that any known algorithm orcalculation may be implemented by the value-congruence module 208 inorder to accomplish the value-congruence operations of the embodiments.

Also, it should be appreciated that a function described herein as beingperformed at a particular module may be performed at one or more othermodules and/or by one or more other devices instead of or in addition tothe function performed at the particular module.

FIG. 3 depicts a data model 300 for organizing and maintaining positiveappraisal data, in accordance with example embodiments. Specifically,the data model 300 may maintain logical relationships and/or physicalrelationships between the various types of positive appraisal data.Subsequently, the UEA system may employ the data model 300 during dataanalysis and determining value-congruence between positive appraisalsand categorized content. In various embodiments, the data model 300 maybe created by the UEA system to include data types, data attributes, anddata relationships. Also, the data model 300 may maintain tables,columns, and keys to support physical data manipulation, for exampleindexing, within databases.

The data model 300 may be comprised of one or more data objectsincluding, positive appraisal experience 305, positive appraisalsensation 310, and positive appraisal category 315. A positive appraisalexperience 305 may be associated with one or more positive appraisalsensations 310. Further, the positive appraisal sensations may bequalitatively and quantitatively analyzed, and thereafter aggregatedaccording to various determined positive appraisal categories 315. Thepositive appraisal categories 315 may serve to characterize the data andlink the described sensations to relevant, or value-congruent, content.In an embodiment, the data structure may be arranged in a hierarchicalstructure. For example, the one or more positive appraisal categories315 may be grouped into an ordered sequence, such as a ranking based ona count of the occurrences. This embodiment may serve to indicate whichtypes of user emotions, or sensations, are exemplified most frequentlyby a particular user. Accordingly, higher ranking positive appraisalcategories 315 may suggest a stronger relevancy between user preferencesand the content.

FIGS. 4A-4B depict a flow chart of a method for performing qualitativelyand quantitatively analysis of user experiences in order to providecontent recommendations, in accordance with an example embodiment. Themethod 400 as shown in FIGS. 4A-4B may be executed or otherwiseperformed by one or a combination of various systems and devices, suchas UEA system 110 as illustrated in FIG. 1, UEA system 200 as depictedin FIG. 2.

At step 405, the UEA system may transmit an electronic message, forexample an email, to a user via a communications network. In the exampleembodiment, a user may receive an invitation to view content andparticipate in an experience assessment associated with the qualitativeand/or quantitative analysis performed according to the embodiments. Theuser may employ a client device, such as desktop computer, that can beconnected to the communications network and run software whichfacilitates communication with the UEA system. According to theembodiments, the electronic message may serve as an invitation toparticipate in one or more experience assessments supported by the UEAsystem. The electronic message may be implemented using variousnetwork-based communication mechanisms, including but not limited to,electronic messaging, instant messaging, Voice Over Internet Protocol(VoIP), email, and the like. In an embodiment, the invitation mayinclude information, such as a consent form, advising the user oftechnological requirements and time constraints associated with the oneor more experience assessments.

At step 410, the UEA system may receive a response from the user toindicate participation in the various experience assessments. In anembodiment, the response may also be a communications network-basedmessage, and may be transmitted via a communications network in asimilar manner to the invitation. The UEA system employs an interfacewith the communications network for electronically receiving theresponse from the user. According to another embodiment, the electronicinvitation may include one or more selectable options that specify theuser's response. Subsequently, the designated response may betransmitted to the UEA system. For example, a Hypertext TransferProtocol (HTTP) link may be included in the electronic message that theuser may select, or “click”, upon choosing to participate in theexperience assessment. Other conventional user input mechanisms may beemployed to communicate the user response to the UEA system, such as,but not limited to, checkboxes, dropdown lists, selectable icons,textboxes, and the like.

At step 415, upon receiving the response, the UEA system may determinewhether the user has selected to participate in the user experienceassessments according to the embodiments. The determination may beaccomplished by employing the processor of the UEA system, for example.In the instance where the UEA system determines that user has positivelyselected to participate in the experience assessment based on theresponse (i.e., “Yes”), the method proceeds to step 420. Otherwise, ifthe UEA system determines that the user has responded to not participatein the experience assessment (i.e., “No”) then the method 400 may end atstep 425. According to the embodiments, ending method 100 may beimplemented using any suitable manner of termination, such as no furtherinteraction with the user, sending a message to the user, or returningto step 405 for a maximum number of iterations.

At step 420, the UEA may initiate a network-based experience assessmentwith the user. In an embodiment, the UEA may initiate the assessment byquerying user to access and consume electronic content that isassociated with an experience assessment. For example, the UEA systemmay transmit a URL in the invitation that allows the user to downloadand view a particular on-line movie. According to example embodiments,the content may be deemed relevant to one or more experienceassessments, and subsequently selected to accompany the assessment. TheUEA may further provide the user with options of viewing supplementarycontent within an optional predetermined time period (e.g., hours, days,etc.). As an example, an electronic invitation can request the user towatch an on-line movie, and later watch two or more additional movieswithin the optional specified time-period of 20 days. The electronicinvitation may additionally include other data regarding requirements,such as technological and system requirements, necessary for the user toparticipate in the qualitative analysis.

According to an embodiment, step 420 may include the UEA systemcommunicating a preliminary assessment. The preliminary assessment maybe a simple evaluation that serves as a baseline for the user'sexperiences and/or sensations. The UEA system may transmit an electronicmessage, such as an email, via a communications network, which containsthe preliminary assessment. Thereafter, the UEA may employ thepreliminary assessment results to qualitatively assesses the user'soverall well-being. Examples of subjective well-being assessmentsinclude, but are not limited to, the Subjective Well-Being Scales whichconsists of the Satisfaction With Life Scale (SWLS), Scale of Positiveand Negative Experiences (SPANE), Flourishing Scale (FS), and the like.Alternatively, other electronic distribution mechanisms, such as anUniform Resource Locator (URL), may be employed to direct the user toone or more baseline assessments supported by the UEA.

In the example embodiment, communications network may be a wiredconnection, a LAN, a WAN, the Internet, or other packet-switched datanetworks. Furthermore, a communications network may support wirelessdata connections. In such an embodiment, Wi-Fi, IEEE 802.11, or anothertype of wireless access points coupled to a data-packet network may beemployed. Accordingly, a variety of different configurations arecontemplated.

At step 430, the UEA system may receive positive appraisal experienceselections from the user. In an embodiment, the UEA system conductsnetwork-based communications, such as a videoconference, to conduct anexperience assessment with the user. The experience assessment may besupported using any one of, or a combination of, the conventionaltelecommunication technologies that allows computer users to exchangeaudio, visual, and multimedia content in real-time. These types oftelecommunication technologies include, but are not limited to,videoconferencing systems, application sharing systems, telephonysystems, electronic meeting systems. Accordingly, during the experienceassessment, the UEA system presents one or more predetermined positiveappraisal experiences to the user. For example, a semi-structuredInternet based videoconference may be used to present the user with alist of one or more positive appraisal experience types.

In an embodiment, the positive appraisal experiences may be related toevents associated with the purchase and/or viewing of various types ofcontent. For instance, the positive appraisal experiences may beassociated with watching a movie, reading a book, attending the theater,and the like. The positive appraisal experiences may be previouslystored in a memory and/or storage device of the UEA system 300. Itshould be appreciated that the predetermined positive appraisalexperiences may be obtained from a sample set of users, collected duringprevious UEA system communications, or selectively entered by anadministrator of the UEA system. Alternatively, any manner of acquiringinformation that is deemed necessary and/or appropriate may be employedby the UEA system to obtain the positive appraisal experiences.

At step 430, a graphical user interface (GUI) may be displayed to theuser during the experience assessment. The GUI may allow the UEA systemto receive various user selections. The received selections may indicateone or more experiences, from the provided list, that are qualitatively“positive” for the particular user. The GUI may present one or moreselection options that correspond to a positive appraisal experiences,in for the user to make a selection. Each option may be represented byan icon and/or text describing the transaction request. In anembodiment, the user may be limited to a maximum and/or minimum numberof positive appraisal experiences that may be selected from thoseprovided. For example, during the experience assessment, the user may berequested to select their “top 3 positive appraisal experiences” from adisplayed list of 50 predetermined positive appraisal experiences.

At step 435, the UEA system receives positive appraisal sensation datafrom the user. In an embodiment, the user may communicate one or morepositive appraisal sensations that correspond to each of the selectedappraisal experiences. Then, the UEA system may perform the qualitativeand quantitative analysis functions of the embodiments using thereceived positive appraisal sensation data. These positive appraisalsensations may be associated with individual emotional reactions, orfeelings, that may be personally experienced and described by the useras a result of the viewing the particular content media. In anotherembodiment, the positive appraisal sensations may correspond toparticular user behavior related to the content experience. Userbehavior may be associated with particular actions performed by theuser, in response to specific events or content. In accordance with theembodiment, user behavior may include, but is not limited to, userpurchasing history, user web browsing history, user content selectionhistory, and the like. In an embodiment, the positive appraisalsensations may be experienced by the user while viewing the on-linemovies, as indicated in the invitation. For instance, after a userselects three positive appraisal experiences (e.g., movies, books,theater) the user may subsequently communicate the sensations describedwhile undergoing the particular experience. Through the user's memory ofa positive experience, specific qualitative data and quantitative datamay be collected and evaluated to further characterize a particularuser's behavior and preferences.

In an embodiment, the positive appraisal sensations received at step 435may include qualitative data. Qualitative data may be comprised ofsubjective scales, psychological sensations, and/or emotions.Qualitative types of positive appraisal sensations may be feelings ofhappiness, fear, or excitement, for example. The qualitative data may bedirectly entered by the user into a user device, such as a personalcomputer. For example, the user may select one or more positiveappraisal sensations using a mouse, a pointing device, or a touch screencomputer display. Subsequently, the positive appraisal sensations may beelectronically transmitted by the user device, via a communicationsnetwork, and received by the UEA system. Alternatively, qualitative datamay be communicated to the UEA system from a source other than the userdevice. For example, an administrator participating in a videoconferenceinterview may enter qualitative data into a portable computing device,such a laptop computer, that may be communicatively coupled to acommunications network, such as the Internet and/or a local areanetwork. According to this embodiment, the qualitative data may beassociated with visually observed behavior (e.g., emotional speech,physical gestures, facial expressions, etc.) by the administrator whilethe user describes a positive appraisal experience. Qualitative data maybe communicatively transmitted via the communications network, andreceived by the UEA system. As should be appreciated, any manner ofacquiring qualitative data that is deemed necessary and/or appropriatemay be employed by the UEA system to receive the qualitative segments ofpositive appraisal sensation data.

According to example embodiments, the positive appraisal sensationsreceived at step 435 may include quantitative data. Quantitative datamay be comprised of physiological measurements that may serve to reflecthuman sensations and biological changes in conjunction with thoughts,emotions, and behavior. Accordingly, the physiological measurements maycomprise quantified physical and/or chemical activities which include,but are not limited to, heart rate, blood pressure, muscle stress, brainactivity, hormones, and other physiological functions as is known in theart. In an embodiment, these physiological functions may be measured toobtain one or more quantitative values, or physiological measurements,that are subsequently associated with positive appraisal sensations. Forexample, a user device may be communicatively coupled to one or morebiofeedback sensors that measure the user's physiological activityduring the experience assessment. Thereafter, the user device transmitsthe quantitative data, such as electrical activity in the brain, to theUEA system as the quantitative portion of the positive appraisalsensation. Examples of biofeedback sensors may include, but are notlimited to electromyographs (EMG), thermometers, electroencephalographs(EEG), sphygmomanometers and the like. The biofeedback sensors may beimplemented within the UEA system as software, firmware, hardware,and/or various combinations thereof. In an embodiment, the biofeedbacksensors may be communicatively coupled to a communications network, suchas the Internet and/or a local area network. As should be appreciated,any manner of acquiring quantitative data that is deemed necessaryand/or appropriate may be employed by the UEA system to receive thequantitative segment of positive appraisal sensation data.

In some embodiments, at step 435, the UEA system may receive one or moreadditional positive appraisal sensation data from the user. Theadditional positive appraisal sensations may be generated from asubjective self-assessment performed by the user. In the embodiment, theadditional positive appraisal sensation data may be employed tosupplement the positive appraisal sensation data resulting from thesystem-generated assessment, initiated in step 420. Accordingly, the UEAsystem may utilize data associated with the self-assessment and/or thesystem-generated for performing qualitative and quantitative analysis.

At step 440, the UEA system may identify one or more positive appraisalcategories. In the example embodiment, the UEA system may performqualitative and/or quantitative analysis on the received positiveappraisal sensation data in order to determine relevancy factors such asrelationships, trends, and characteristics that may be employed tofurther aggregate and apply the received data. In some embodiments, theUEA system may operate to determine one or more positive appraisalcategories that correspond with each of the user's positive appraisalsensations. Alternatively, the positive appraisal sensations may begrouped, or otherwise aggregated, in order to identify one or morepositive appraisal categories that may be indicated by the relevancyfactors. The positive appraisal categories may be classifications thatcharacterize the types of behavior and/or emotions that may furtherindicate preferences for the particular user. For example, a positiveappraisal category of “humor” may be determined from analyzing thesensations of laughter and warmth triggered by watching an on-linemovie.

In an embodiment, the positive appraisal categories may be associatedwith one or more character strength values. A character strength valuemay be one or more characteristics employable by the UEA system todescribe the behavior and/or emotions of the user. Furthermore, acharacter strength value may indicate a recognized pattern or trend,which may be suggestive of the user's behavior and/or emotions. Anexample of a character strength may be “bravery”, for example.

At step 445, the UEA system may determine rankings associated with thepositive appraisal categories. In an example embodiment, the rank may bedetermine based on the frequency for each identified positive appraisalcategory. The UEA system may calculate the number of occurrencescorresponding to each identified positive appraisal category. Forinstance, the UEA system may count each time a positive appraisalcategory of “humor” was identified during the experience of watching anon-line movie. The number of occurrences for an identified positiveappraisal category may be calculated spanning the entire assessment, ormultiple assessments. The UEA system may assign ranks directly based ona the calculated number of occurrences. For instance, 100 or moreoccurrences may receive rank of 1, 50 to 99 occurrences may receive arank of 2, and so forth. Alternatively, the positive appraisalcategories may be ranked in the relation to each other. In someembodiments, the positive appraisal categories may be arranged in asequential order that is either ascending or descending, based on thefrequency, and subsequently assigned a rank corresponding to the order.According to the embodiment, higher rankings may be an indication ofincreased relevancy of the positive appraisal category to the user'spreferences.

At step 450, the UEA system may generate a recommendation profile forthe user. One or more recommendation profiles may be generated thatcorrespond to each user of the UEA system. A recommendation profile maycomprise positive appraisal categories associated with the user. In theexample embodiment, the recommendation profile may be comprised of apredetermined number of positive appraisal categories with the highestrankings. For example, positive appraisal categories with the user's“top 5” rankings may be included in the generated recommendationprofile. In some embodiments, the recommendation profile may compriseany combination of positive appraisal data resulting from thequalitative and/or quantitative analysis performed by the UEA system.Thus, the recommendation profile may be employed for maintaininguser-specific data relevant to the user's preferences, and therebysuitable for predicting relevant content. In some embodiments, the UEAsystem may update the recommendation profile at one or morepredetermined intervals, such as every 30 days.

In an embodiment, the UEA system may access previously createdrecommendation profiles. The UEA system may operate to upload, orotherwise retrieve, a dataset the may contain one or more predeterminedrecommendation profiles that have been created using the assessmentand/or analysis functionalities of the embodiments. Thus, thepredetermined recommendation profiles may contain positive appraisalcategories that may serve to characterize the correspondingpredetermined users. Subsequently, the UEA system may further evaluateand/or analyze the recommendation profile created in step 450 accordingto the one or more previously created recommendation profiles. In anembodiment, the UEA system may perform a matching of the createdrecommendation profiles and the predetermined recommendation profiles.Accordingly, the UEA system may also determine value-congruence withusers that have been previously assessed or otherwise previouslyinteracted with the system.

At step 455, the UEA system may operate to match the recommendationprofile to one or more categorized content. In various embodiments, eachcontent category may correspond to a positive appraisal categoryemployed by the UEA system. A content category may serve to characterizethe content. Furthermore, a category may be indicative of a relationshipbetween the content and particular user behavior and/or emotions. Eachelement of electronic content may be stored with one or more associatedcodes. The code may indicate a category, and subsequently a positiveappraisal category, that corresponds to the content. For instance, anonline movie may be coded to the “humor” category. The code may beimplemented as an electronic indicator, such as a bit. In an embodiment,the content may be categorized by a trusted source, such as anassessment administrator or the content provided.

According to example embodiments, the UEA may determinevalue-congruence, or matches, between content and recommendationprofiles that correspond to the same user behavior and/or emotions.Therefore, the UEA system functions to determine user relevant content,based on these factors. The UEA system may recognize a match between theonline movie coded to the “humor” and the recommendation profilecomprising the positive appraisal category “humor”, for example. In anembodiment, the UEA system may search for matching content.Particularly, the UEA system may iteratively conduct matching operationsfor each content element stored by the system. In another embodiment,the system may selectively conduct matching operations on particularcontent elements, such as content requested by the user.

At step 460, the UEA system may transmit one or more contentrecommendations to the user. Based on the matches determined by the UEAsystem in step 455, the system may generate content recommendationinformation to be presented to the user. The content recommendationinformation may include one or more indications that serve to indicate,or otherwise represent, content determined to be relevant to the user.Examples of indications may include, but are not limited to lists, HTTPlinks, URLs, descriptions, icons, thumbnails and the like. The UEAsystem may recommend each content element and/or a portion of thecontent elements that match a user's recommendation. According toexample embodiments, the UEA system may generate an electronic message,such as an email, that includes the content recommendation information.Thereafter, the user computer may receive and display the contentrecommendation message, including the list of recommended content, tothe user. In some embodiments, the content recommendation transmitted tothe user may also include the content, itself. In an alternativeembodiment, the content recommendation may include a mechanism to accessor download the content. The UEA system may transmit the recommendationinformation to a user via a communications network. It should beappreciated that the UEA system may employ any known mechanism fortransmitting, or otherwise conveying, the content recommendations to theuser.

In another embodiment, the content recommendations may be transmitted,or otherwise conveyed, to one or more data sources from the UEA system.Thereafter, the content recommendations may be employed by the one ormore data sources, so as to accomplish personalization of datadistributed to the particular user. For instance, a data source whichprovides a webpage, may receive one or more content recommendationsassociated with a user. Accordingly, the data source may employ thecontent recommendations to particularly include and/or exclude datadisplayed by the webpage based on the user relevancy, as a result of thereceived content recommendation.

Hereinafter, physical aspects of implementation of the exampleembodiments will be described. As described above, example methods maybe computer implemented as a system. The system or portions of thesystem may be in the form of a “processing machine,” for example. Asused herein, the term “processing machine” is to be understood toinclude at least one processor that uses at least one memory. The atleast one memory stores a set of instructions. The instructions may beeither permanently or temporarily stored in the memory or memories ofthe processing machine. The processor executes the instructions that arestored in the memory or memories in order to process data. The set ofinstructions may include various instructions that perform a particulartask or tasks, such as those tasks described above in the flowcharts.Such a set of instructions for performing a particular task may becharacterized as a program, software program, or simply software.

The description of example embodiments describes servers, portableelectronic devices, and other computing devices that may include one ormore modules, some of which are explicitly depicted in the figures,others are not. As used herein, the term “module” may be understood torefer to executable software, firmware, hardware, and/or variouscombinations thereof. It is noted that the modules are example. Themodules may be combined, integrated, separated, and/or duplicated tosupport various applications. Also, a function described herein as beingperformed at a particular module may be performed at one or more othermodules and/or by one or more other devices (e.g., servers) instead of,or in addition to, the function performed at the particular module.Further, the modules may be implemented across multiple devices and/orother components local or remote to one another. Additionally, themodules may be moved from one device and added to another device, and/ormay be included in both devices. It is further noted that the softwaredescribed herein may be tangibly embodied in one or more physical media,such as, but not limited to, a compact disc (CD), a digital versatiledisc (DVD), a floppy disk, a hard drive, read only memory (ROM), randomaccess memory (RAM), as well as other physical media capable of storingsoftware and/or combinations thereof. Moreover, the figures illustratevarious components (e.g., servers, portable electronic devices, clientdevices, computers, etc.) separately. The functions described as beingperformed at various components may be performed at other components,and the various components may be combined and/or separated. Othermodifications also may be made.

According to example embodiments, the systems and methods may becomputer implemented using one or more computers, incorporating computerprocessors. The computer implementation may include a combination ofsoftware and hardware. The computers may communicate over a computerbased network. The computers may have software installed thereonconfigured to execute the methods of the example embodiments. Thesoftware may be in the form of modules designed to cause a computerprocessor to execute specific tasks. The computers may be configuredwith hardware to execute specific tasks. As should be appreciated, avariety of computer based configurations are possible.

The processing machine described above may also utilize any of a widevariety of other technologies including a special purpose computer, acomputer system including a microcomputer, mini-computer or mainframe,for example, a programmed microprocessor, a micro-controller, a PICE(peripheral integrated circuit element), a CSIC (Customer SpecificIntegrated Circuit) or ASIC (Application Specific Integrated Circuit) orother integrated circuit, a logic circuit, a digital signal processor, aprogrammable logic device such as a FPGA, PLD, PLA or PAL, or any otherdevice or arrangement of devices, for example, capable of implementingthe steps of the process.

It is appreciated that in order to practice the methods as describedabove, it is not necessary that the processors and/or the memories ofthe processing machine be physically located in the same geographicalplace. For example, each of the processors and the memories and the datastores used may be located in geographically distinct locations andconnected so as to communicate in any suitable manner. Additionally, itis appreciated that each of the processor and/or the memory and/or datastores may be composed of different physical pieces of equipment.Accordingly, it is not necessary that the processor be one single pieceof equipment in one location and that the memory be another single pieceof equipment in another location. For example, it is contemplated thatthe processor may be two or more pieces of equipment in two or moredifferent physical locations. These two or more distinct pieces ofequipment may be connected in any suitable manner. Additionally, thememory may include two or more portions of memory in two or morephysical locations. Additionally, the data storage may include two ormore components or two or more portions of memory in two or morephysical locations.

To explain further, processing as described above is performed byvarious components and various memories. However, it is appreciated thatthe processing performed by two distinct components as described abovemay, in accordance with further embodiments, be performed by a singlecomponent. Further, the processing performed by one distinct componentas described above may be performed by two distinct components. In asimilar manner, the memory storage performed by two distinct memoryportions as described above may, in accordance with a furtherembodiment, be performed by a single memory portion. Further, the memorystorage performed by one distinct memory portion as described above maybe performed by two memory portions. It is also appreciated that thedata storage performed by two distinct components as described abovemay, in accordance with a further embodiment, be performed by a singlecomponent. Further, the data storage performed by one distinct componentas described above may be performed by two distinct components.

As described above, a set of instructions is used in the processing ofvarious embodiments. The set of instructions may be in the form of aprogram or software. The software may be in the form of system softwareor application software, for example. The software might also be in theform of a collection of separate programs, a program module within alarger program, or a portion of a program module, for example. Thesoftware used might also include modular programming in the form ofobject oriented programming or any other suitable programming form. Thesoftware tells the processing machine what to do with the data beingprocessed.

Further, it is appreciated that the instructions or set of instructionsused in the implementation and operation of the various embodiments maybe in a suitable form such that the processing machine may read theinstructions. For example, the instructions that form a program may bein the form of a suitable programming language, which is converted tomachine language or object code to allow the processor or processors toread the instructions. For example, written lines of programming code orsource code, in a particular programming language, are converted tomachine language using a compiler, assembler or interpreter. The machinelanguage is binary coded machine instructions that are specific to aparticular type of processing machine, e.g., to a particular type ofcomputer, for example. The computer understands the machine language.

Any suitable programming language may be used in accordance with thevarious embodiments. Illustratively, the programming language used mayinclude assembly language, ActionScript, Ada, APL, Basic, C, C++, C#,COBOL, Ceylon, Dart, dBase, F#, Fantom, Forth, Fortran, Go, Java,Jquery, Modula-2, .NET, Objective C, Opa, Pascal, Prolog, Python, RUMRuby, Visual Basic, X10, and/or JavaScript, for example. Further, it isnot necessary that a single type of instructions or single programminglanguage be utilized in conjunction with the operation of the system andmethod of various embodiments. Rather, any number of differentprogramming languages may be utilized as is necessary or desirable.

Also, the instructions and/or data used in the practice of the variousembodiments may utilize any compression or encryption technique oralgorithm, as may be desired. An encryption module might be used toencrypt data. Further, files or other data may be decrypted using asuitable decryption module, for example.

As described above, various embodiments may illustratively be embodiedin the form of a processing machine, including a computer or computersystem, for example, that includes at least one memory. It is to beappreciated that the set of instructions, e.g., the software, forexample, that enables the computer operating system to perform theoperations described above, may be contained on any of a wide variety ofcomputer readable media, as desired. Further, the data, for example,processed by the set of instructions might also be contained on any of awide variety of media or medium. For example, the particular medium,e.g., the memory in the processing machine, utilized to hold the set ofinstructions and/or the data used, may take on any of a variety ofphysical forms or transmissions. Illustratively, the medium may be inthe form of paper, paper transparencies, a compact disk, a DVD, anintegrated circuit, a hard disk, a floppy disk, an optical disk, amagnetic tape, a RAM, a ROM, a PROM, a EPROM, a wire, a cable, a fiber,communications channel, a satellite transmissions or other remotetransmission, as well as any other medium or source of data that may beread by the processors of the system.

Further, the memory or memories used in the processing machine thatimplements the various embodiments may be in any of a wide variety offorms to allow the memory to hold instructions, data, or otherinformation, as is desired. Thus, the memory might be in the form of adatabase to hold data. The database might use any desired arrangement offiles such as a flat file arrangement or a relational databasearrangement, for example.

In the system and method of the various embodiments, a variety of “userinterfaces” may be utilized to allow a user to interface with theprocessing machine or machines that are used to implement variousembodiments. As used herein, a user interface includes any hardware,software, or combination of hardware and software used by the processingmachine that allows a user to interact with the processing machine. Auser interface may be in the form of a dialogue screen, for example. Auser interface may also include any of a mouse, touch screen, keyboard,voice reader, voice recognizer, dialogue screen, menu box, list,checkbox, toggle switch, a pushbutton or any other device that allows auser to receive information regarding the operation of the processingmachine as it processes a set of instructions and/or provide theprocessing machine with information. Accordingly, the user interface isany device that provides communication between a user and a processingmachine. The information provided by the user to the processing machinethrough the user interface may be in the form of a command, a selectionof data, or some other input, for example.

As discussed above, a user interface is utilized by the processingmachine that performs a set of instructions such that the processingmachine processes data for a user. The user interface is typically usedby the processing machine for interacting with a user either to conveyinformation or receive information from the user. However, it should beappreciated that in accordance with some embodiments of the system andmethod, it is not necessary that a human user actually interact with auser interface used by the processing machine. Rather, it iscontemplated that the user interface might interact, e.g., convey andreceive information, with another processing machine, rather than ahuman user. Accordingly, the other processing machine might becharacterized as a user. Further, it is contemplated that a userinterface utilized in the system and method may interact partially withanother processing machine or processing machines, while alsointeracting partially with a human user.

While the various embodiments have been particularly shown and describedwithin the UEA system, it will be appreciated that variations andmodifications may be effected by a person of ordinary skill in the artwithout departing from the scope of the various embodiments.Furthermore, one of ordinary skill in the art will recognize that suchprocesses and systems do not need to be restricted to the specificembodiments described herein. Other embodiments, combinations of thepresent embodiments, and uses and advantages will be apparent to thoseskilled in the art from consideration of the specification and practiceof the various embodiments disclosed herein. The specification andexamples should be considered example.

Accordingly, while the various embodiments are described here in detailin relation to the example embodiments, it is to be understood that thisdisclosure is only illustrative and example and is made to provide anenabling disclosure. Accordingly, the foregoing disclosure is notintended to be construed or to limit the various embodiments orotherwise, to exclude any other such embodiments, adaptations,variations, modifications, and equivalent arrangements.

What is claimed is:
 1. A method, comprising: initiating, by one or morecomputing devices, a user experience assessment with a user computer viaa communications network, wherein the user experience assessmentcomprises one or more predetermined content consuming experiences;receiving, by the one or more computing devices, positive appraisalsensation data from the user computer, wherein the positive appraisalsensation data comprises user responses associated with the one or morepredetermined content consuming experiences; using, by the one or morecomputing devices, one or more analysis algorithms in order to analyzethe positive appraisal sensation data; determining, by the one or morecomputing devices, one or more positive appraisal categoriescorresponding to the positive appraisal sensation data, wherein the oneor more positive appraisal categories are determined based on theanalysis; ranking, by the one or more computing devices, each of the oneor more positive appraisal categories based on a predetermined frequencyfor each of the one or more positive appraisal categories, wherein theone or more positive appraisal categories are arranged in a sequentialorder based on the ranking; generating, by the one or more computingdevices, a recommendation profile associated with a user, wherein therecommendation profile comprises the one or more positive appraisalcategories each associated with the ranking; determining, by the one ormore computing devices, value-congruency between the recommendationprofile and coded content based on at least a predetermined number ofmatches between the recommendation profile and the coded content or atleast a predetermined fraction or threshold indicative of a requiredlevel of similarity between the recommendation profile and the codedcontent, wherein the coded content is based at least upon informationretrieved from scanned text; generating, by the one or more computingdevices, content recommendation information based on the determinedvalue-congruency; and transmitting, by the one or more computingdevices, an electronic message to the user via the communicationsnetwork, wherein the electronic message comprises the contentrecommendation information.
 2. The method of claim 1, wherein thepositive appraisal sensation data comprises psychological activityassociated with the user in response to the one or more predeterminedcontent consuming experiences.
 3. The method of claim 1, wherein thepositive appraisal sensation data comprises physiological activityassociated with the user in response to the one or more predeterminedcontent consuming experiences.
 4. The method of claim 3, furthercomprising: receiving, by the one or more computing devices, one or moremeasurements associated with the physiological activity, wherein the oneor more measurements are obtained by a biofeedback sensor.
 5. The methodof claim 1, wherein the coded content is associated with one or morepredetermined content categories.
 6. The method of claim 5, whereindetermining the value-congruency comprises identifying one or morepositive appraisal categories that correspond to the one or morepredetermined content categories.
 7. The method of claim 1, wherein thecoded content has been automatically data mined from one or more contentproviders via the communications network.
 8. The method of claim 7,wherein the coded content has been aggregated into one or moredetermined content categories according to characteristics as a resultof evaluating the data mined content.
 9. A system, comprising: acommunications network; a user computer commutatively coupled to thecommunications network; and one or more computing devicescommunicatively coupled to the communications network, wherein the oneor more computing devices operate to: initiate a user experienceassessment with the user computer via the communications network,wherein the user experience assessment comprises one or morepredetermined content consuming experiences; receive positive appraisalsensation data from the user computer, wherein the positive appraisalsensation data comprises user responses associated with the one or morepredetermined content consuming experiences; use one or more analysisalgorithms in order to analyze the positive appraisal sensation data;determine one or more positive appraisal categories corresponding to thepositive appraisal sensation data, wherein the one or more positiveappraisal categories are determined based on the analysis; rank each ofthe one or more positive appraisal categories based on a predeterminedfrequency for each of the one or more positive appraisal categories,wherein the one or more positive appraisal categories are arranged in asequential order based on the ranking; generate a recommendation profileassociated with a user, wherein the recommendation profile comprises theone or more positive appraisal categories each associated with theranking; determine value-congruency between the recommendation profileand coded content based on at least a predetermined number of matchesbetween the recommendation profile and the coded content or at least apredetermined fraction or threshold indicative of a required level ofsimilarity between the recommendation profile and the coded content,wherein the coded content is based at least upon information retrievedfrom scanned text; generate content recommendation information based onthe determined value-congruency; and transmit an electronic message tothe user computer via the communications network, wherein the electronicmessage comprises the content recommendation information.
 10. The systemof claim 9, wherein the positive appraisal sensation data comprisespsychological activity associated with the user in response to the oneor more predetermined content consuming experiences.
 11. The system ofclaim 9, wherein the positive appraisal sensation data comprisesphysiological activity associated with the user in response to the oneor more predetermined content consuming experiences.
 12. The system ofclaim 11, further comprising: a biofeedback sensor communicativelycoupled to the user computer devices, wherein the biofeedback sensorobtains one or more measurements associated with the physiologicalactivity.
 13. The system of claim 9, wherein the coded content isassociated with one or more predetermined content categories.
 14. Thesystem of claim 13, wherein the one or more computing devices furtheroperate to: identify one or more positive appraisal categories thatcorrespond to the one or more predetermined content categories, in orderto determine the value-congruency.
 15. The system of claim 14, whereinthe coded content has been aggregated into one or more determinedcontent categories according to characteristics as a result ofevaluating the data mined content.